Remote Sensing Retrieval of Isoprene Concentrations in the Southern Ocean
Bibliographic record
Abstract
Abstract Isoprene produced by marine phytoplankton acts as a precursor of secondary organic aerosol and thereby affects cloud formation and brightness over the remote oceans. Yet the marine isoprene emission is poorly constrained, with discrepancies among estimates that reach 2 orders of magnitude. Here we present ISOREMS, the first satellite‐only based algorithm for the retrieval of isoprene concentration in the Southern Ocean. Sea surface concentrations from six cruises were matched with remotely sensed variables from MODIS Aqua, and isoprene was best predicted by multiple linear regression with chlorophyll a and sea surface temperature. Climatological (2002–2018) isoprene distributions computed with ISOREMS revealed high concentrations in coastal and near‐island waters, and within the 40–50°S latitudinal band. Isoprene seasonality paralleled phytoplankton productivity, with annual maxima in summer. The annual Southern Ocean emission of isoprene was estimated at 63 Gg C yr −1 . The algorithm can provide spatially and temporally realistic inputs to atmospheric and climate models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".